Defining cost functions for adaptive steganography at the microscale
Kejiang Chen, Weiming Zhang, Hang Zhou, Nenghai Yu, Guorui Feng · 2016
In the framework of minimizing embedding distortion steganography, the definition of cost function almost determines the security of the method. Generally speaking, texture areas would be assigned low cost, while smooth areas with high cost. However, the prior methods are still not precise enough to capture image details. In this paper, we present a novel scheme of defining cost function for adaptive steganography at the microscale. The proposed scheme is designed by using a “microscope” to highlight fine details in an image so that distortion definition can be more refined. Experiments show that by adopting our scheme, the current steganographic methods (WOW, UNIWARD, HILL) will achieve better performances on resisting the state-of-the-art steganalysis.